JP5539876B2 - Consumer experience assessment device - Google Patents
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- JP5539876B2 JP5539876B2 JP2010523112A JP2010523112A JP5539876B2 JP 5539876 B2 JP5539876 B2 JP 5539876B2 JP 2010523112 A JP2010523112 A JP 2010523112A JP 2010523112 A JP2010523112 A JP 2010523112A JP 5539876 B2 JP5539876 B2 JP 5539876B2
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Description
［関連特許出願］
本出願は、「Ｔｏｔａｌ Ｃｏｎｓｕｍｅｒ Ｅｘｐｅｒｉｅｎｃｅ Ａｓｓｅｓｓｍｅｎｔ Ｓｙｓｔｅｍ」の題名でＡｎａｎｔｈａ Ｐｒａｄｅｅｐ， Ｒｏｂｅｒｔ Ｔ． Ｋｎｉｇｈｔ， ａｎｄ Ｒａｍａｃｈａｎｄｒａ Ｇｕｒｕｍｏｏｒｔｈｙによって２００７年８月２８日に提出された米国暫定特許出願６０／９６８５６０号を基に優先権を主張するものである。
[Related patent applications]
This application is entitled “Total Consumer Experience Assessment System” by Ananta Pradeep, Robert T. et al. Priority is claimed on the basis of US Provisional Patent Application No. 60 / 968,560 filed Aug. 28, 2007 by Knight, and Ramachandra Gurumoorthy.
［発明の技術分野］
此処に開示するものは消費者経験査定装置に関する。
[Technical Field of the Invention]
What is disclosed herein relates to a consumer experience assessment device.
消費者の経験を推定するための従来の装置は限定的なものであった。消費者経験査定装置の或るものは人口統計的情報、統計的データ、及び調査に基づく応答の収集によるものであるが、従来のシステムは意味論的、統語論的、隠喩的、文化的、及び、解釈法的の誤謬に影響される。 Conventional devices for estimating consumer experience have been limited. Some consumer experience assessment devices rely on collecting demographic information, statistical data, and survey-based responses, while traditional systems are semantic, syntactic, metaphorical, cultural, And affected by legal errors in interpretation.
従って、消費者の経験を推定し査定するための改善された方法及び装置が望まれて居る。 Accordingly, an improved method and apparatus for estimating and assessing consumer experience is desired.
特種な実施例を示す以下の図を参照することによって、発明の開示は容易に理解されることであろう。 The disclosure of the invention will be readily understood by reference to the following figures, which illustrate specific embodiments.
本発明を実施するに当たり、発明者が最良とみなす形体を含めた実施例を、爾後詳細に参照することにする。これらの特種実施例は添付された図に示されてある。本発明はこれらの実施例によって記述されるものではあるが、本発明はこれらの実施例によって限定されるものではなく、後述の請求項で定義されるように、本発明の精神に則った代案、変化案、均等案などを含むものとする。 In practicing the present invention, reference will now be made in detail to the examples, including the features that the inventor deems best. These special embodiments are shown in the accompanying figures. While the invention is described by these examples, the invention is not limited by these examples, and is an alternative in the spirit of the invention as defined in the following claims. , Including changes, changes, etc.
例えば、本発明のテクニク及び機構などは中枢神経系、自律神経系、及び作動体データのような特種のデータに関して記述されるが、本発明のテクニクや機構などは、異なる各種のデータに応用されるものと銘記されるべきものである。各種の機構やテクニクは各種の刺激に応用されるものであることに留意されるべきものである。爾後の記述に於いては、本発明が十分に理解されるべく、詳細な実施例が開示される。これら特種な詳細例には、特種の実施に使用されないものも含まれる。別の例として、本発明の実際の内容を不明確にしない目的から、周知の工程作動などの記述は割愛することとする。 For example, the techniques and mechanisms of the present invention are described with respect to specific data such as central nervous system, autonomic nervous system, and actuator data, but the techniques and mechanisms of the present invention are applied to various different data. Should be inscribed. It should be noted that various mechanisms and techniques apply to various stimuli. In the following description, detailed embodiments are disclosed in order to provide a thorough understanding of the present invention. These special details also include those that are not used in a particular implementation. As another example, for the purpose of not obscuring the actual contents of the present invention, descriptions of well-known process operations will be omitted.
又、本発明に於ける各種のテクニクや機構は明確化のために単数形で記述されることがあるが、特に断って居ない実施例の場合にはテクニクが複数回繰り返されたり、機構が複数回の具体化をされることがあると留意されるべきものである。一例として、システムとは処理装置を多くの状況下で使用するものであるが、特に断りのない限り、本発明によるシステムは複数個の処理装置を有するものであってもよいと理解すべきものである。更に、本発明のテクニクや機構は二個の物体の接続を記述する場合があるが、二個の物体の接続とは必ずしもこれら二個の物体が途中邪魔されることなしに直接接続されると言う意味ではない。一例として、処理装置はメモリに接続されると言っても、その処理装置とメモリの間に各種のブリッジとか制御装置が介在することもあり得るのである。即ち、接続と言うのは、特筆されない限り、途中に介在するもののない直接の接続を意味するものではない。 In addition, various techniques and mechanisms in the present invention may be described in a singular form for the sake of clarity. However, in the case of an embodiment not particularly specified, the technique may be repeated a plurality of times or the mechanism may be It should be noted that there may be multiple implementations. As an example, a system is one that uses processing equipment in many situations, but unless otherwise noted, it should be understood that the system according to the present invention may have multiple processing equipment. is there. Furthermore, the technique or mechanism of the present invention may describe the connection of two objects, but the connection of two objects is not necessarily when these two objects are directly connected without being interrupted. It doesn't mean that. As an example, although a processing device is connected to a memory, various bridges or control devices may be interposed between the processing device and the memory. That is, the connection does not mean a direct connection without any intervening unless otherwise specified.
概要 Overview
システムは製品、サービス、提供物、及び刺激に曝された消費者の神経応答測定を評価して、消費者の経験を査定する。神経応答測定の例には、脳波記録法（ＥＥＧ）、電気皮膚応答（ＧＳＲ）、心電図（ＥＫＧ）、眼電図法（ＥＯＧ）、眼球追跡（ｅｙｅ ｔｒａｃｋｉｎｇ）、及び顔面感情記号化尺度が含まれる。消費者経験の成分は解析され、各成分に独特な神経応答が査定される。多くの場合、神経応答データは他のデータと結合され、解析されて、消費者の総経験が決定される。 The system evaluates the consumer's experience by evaluating the neural response measurements of consumers exposed to products, services, offers, and stimuli. Examples of neural response measurements include electroencephalography (EEG), electrodermal response (GSR), electrocardiogram (EKG), electrooculography (EOG), eye tracking, and facial emotion symbolization scale. . The components of consumer experience are analyzed and a unique neural response is assessed for each component. In many cases, neural response data is combined with other data and analyzed to determine the total consumer experience.
実施例 Example
典型的に消費者経験査定システムは完璧な経験に対するフルな応答を評価するものである。経験には製品、サービス、提供物、及び／或は刺激が関与する。例えば一つの経験にはソーダの缶を買い、そのソーダの缶を手に持ち、その缶の開けられる音を聞き、泡の音を聞き、ソーダの匂いを嗅ぎ、缶の温度を感じ、ソーダを最初に口にし、飲料を味わい、二口目を口にし、などが関与する。従来の消費者経験査定システムは人口統計的情報、統計的情報、及び調査に基づく応答収集によって消費者応答を評価する。従来の消費者経験査定システムについての問題の一つは、経験の成分への応答を正確に測定しないと言うことである。これらには更に意味論的、統語論的、隠喩的、文化的、及び、解釈法的の誤謬が起こり易く、正確に繰り返し可能的に消費者の経験を査定することが阻まれる。 Typically, a consumer experience assessment system evaluates the full response to a perfect experience. Experience involves products, services, offers, and / or stimuli. For example, one experience is buying a soda can, holding the soda can in your hand, listening to the sound of opening the can, listening to the sound of bubbles, smelling the soda, feeling the temperature of the can, The first is the mouth, the beverage is tasted, the second is the mouth, and so on. Traditional consumer experience assessment systems evaluate consumer responses by collecting responses based on demographic information, statistical information, and surveys. One problem with conventional consumer experience assessment systems is that they do not accurately measure the response to experience components. These are also more prone to semantic, syntactic, metaphorical, cultural, and interpretive errors and prevent accurate and repeatable assessment of consumer experience.
従来のシステムは使用者応答の推定に神経行為的及び神経生理学的応答混成明示を使用せず、刺激に対する個別にカストマイズされた神経生理学的及び／或は神経行為的応答を引き出すものでもない。 Prior systems do not use mixed neuroactive and neurophysiological manifestations to estimate user response, nor do they derive individually customized neurophysiological and / or neuroactive responses to stimuli.
従来例の装置は複数のデータセット、個人及びモダリティに亘り複数のデータセット及び複数モード応答の混合提示を混合し、消費者経験査定を開示したり確認することはない。 Conventional devices mix mixed presentations of multiple data sets and multiple mode responses across multiple data sets, individuals and modalities, and do not disclose or confirm consumer experience assessments.
この観点に於いて、本発明による神経生理学的及び神経行為的消費者経験査定システムは従来例の概念及び従来技術のデザインと著しく相違するものであり、それによって、消費者経験の種々の成分への消費者経験の神経生理学的及び神経行為的応答に基づく尺度を与えるべく開発された装置を提供するものである。消費者経験には通信、概念、経験、伝言、画像、オーディオ、価格設定、包装を含み、しかもそれに限定されないマーケティング、広告、及びその他の聴覚的／視覚的／触覚的／嗅覚的刺激を含む。 In this regard, the neurophysiological and neuroactive consumer experience assessment system according to the present invention is significantly different from the prior art concept and prior art design, thereby leading to various components of consumer experience. A device developed to give a measure based on the neurophysiological and neuroactive responses of the consumer experience. Consumer experience includes marketing, advertising, and other audio / visual / tactile / olfactory stimuli, including but not limited to communications, concepts, experiences, messages, images, audio, pricing, packaging.
本発明のテクニクと機構とは、消費者経験査定を改善する目的により、中枢神経系システム、自律神経系システム、及び作動体測定のような神経応答測定を使用する。中枢神経系システム測定機構の例には機能的磁気共鳴画像処理（ｆＭＲＩ）及び脳波記録法（ＥＥＧ）が含まれる。ｆＭＲＩは神経活動の増加に関連する脳での血液酸化を測量するものであるが、現行ｆＭＲＩの実施に於いては時間的分解能が数秒であり良好ではない。ＥＥＧはミリ秒の領域で起こるシナプス後電流に関する電気的活動を測定するものである。頭蓋下ＥＥＧは骨や皮膚の層が広範囲の周波数領域に於いて脆弱化するので、電気的活動を最も正確に測定することが出来る。しかし適当に解析されるならば表面ＥＥＧによって豊富な電気生理学的情報を得ることが可能である。乾燥電極を有する携帯用ＥＥＧでも、多量の神経応答情報が提供される。 The techniques and mechanisms of the present invention use neural response measurements such as central nervous system, autonomic nervous system, and actuator measurements for the purpose of improving consumer experience assessment. Examples of central nervous system measurement mechanisms include functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Although fMRI measures blood oxidation in the brain associated with increased neuronal activity, current resolution of fMRI is not good, with a temporal resolution of a few seconds. EEG measures electrical activity related to post-synaptic currents that occur in the millisecond range. Subcranial EEG provides the most accurate measurement of electrical activity because bone and skin layers weaken in a wide range of frequencies. However, if analyzed properly, abundant electrophysiological information can be obtained by surface EEG. Even a portable EEG with a dry electrode provides a great deal of neural response information.
自律神経系システム測定機構には電気皮膚応答（ＧＳＲ）、心電図（ＥＫＧ）、瞳孔拡張などが含まれる。作動体測定機構には眼電図法（ＥＯＧ）、眼球追跡、顔面感情記号化、反応時間などが含まれる。 Autonomic nervous system measurement mechanisms include electrical skin response (GSR), electrocardiogram (EKG), pupil dilation, and the like. Actuator measurement mechanisms include electrooculography (EOG), eye tracking, facial emotion symbolization, reaction time, and the like.
種々の実施例に於いて、本発明のテクニク及び機構は、認知前（ｐｒｅｃｏｇｎｉｔｉｖｅ）神経的特徴の複数のモード及び明示を、認知的（ｃｏｇｎｉｔｉｖｅ）神経的特徴及び認知後（ｐｏｓｔ ｃｏｇｎｉｔｉｖｅ）神経的特徴に賢明に混合し、より正確に消費者経験査定を実施する。或る例に於いては、自律神経系システム尺度そのものが中枢神経系システム尺度の確認に使用される。作動体及び行為的応答はその他の尺度と混合や結合がされる。種々の実施例に於いて、中枢神経系システム、自律神経系システム、及び作動体システム尺度は完璧な消費者経験を査定する或る尺度へと集成される。 In various embodiments, the techniques and mechanisms of the present invention provide for multiple modes and manifestations of precognitive neural features, cognitive neural features and post-cognitive neural features. Wisely mix and conduct more accurate consumer experience assessments. In some examples, the autonomic nervous system scale itself is used to confirm the central nervous system scale. Actuators and behavioral responses are mixed and combined with other measures. In various embodiments, the central nervous system, autonomic nervous system, and actuator system measures are assembled into a measure that assesses a complete consumer experience.
特種実施例に於いて、被験者は刺激材料に露出され、中枢神経系システム、自律神経系システム、及び作動体データのようなデータは露出の間に収集される。種々の実施例に於いて、製品、サービス、提供物、及び刺激の種々の成分の消費者経験を査定するためにデータが収集される。例えばサンドイッチを食べることに関連する消費者経験には、内容物を集めること、サンドイッチを拵えること、サンドイッチを見たり嗅いだりすること、サンドイッチに噛み付くこと、サンドイッチを味わうこと、などの成分が含まれる。被験者がサンドイッチを食べている他人を眺めている場合には、その他の成分が含まれてもよい。例えば、他の人を見て居る場合の消費者経験には、他人がサンドイッチを食べているのを見ること、噛む音を聞くことなどの成分が含まれてもよい。各種の成分や観点に対する神経応答の重要性や顕著性は有意義的に異なるものであり得る。種々の実施例に於いて、或る経験を示すビデオストリームには種々の成分のための神経応答データを入れる為に注釈付けをすることが出来る。 In a particular embodiment, the subject is exposed to the stimulating material and data such as central nervous system, autonomic nervous system, and actuator data is collected during the exposure. In various embodiments, data is collected to assess the consumer experience of various components of products, services, offers, and stimuli. For example, the consumer experience associated with eating a sandwich includes ingredients such as collecting the contents, picking up the sandwich, watching or sniffing the sandwich, biting the sandwich, tasting the sandwich, etc. It is. If the subject is looking at someone eating a sandwich, other ingredients may be included. For example, a consumer experience when watching another person may include ingredients such as watching another person eating a sandwich, listening to a biting sound. The importance and saliency of neural responses to various components and aspects can be significantly different. In various embodiments, a video stream showing some experience can be annotated to include neural response data for various components.
特種の実施例に於いて、特定のイベント関係電位（ＥＲＰ）解析及び／或はイベント関係電力スペクトル摂動（ＥＲＰＳＰ）が、被験者が刺激に露出される前と被験者が刺激に露出された後毎回の両方に於いて脳の異なる領域で推定される。 In particular embodiments, a specific event-related potential (ERP) analysis and / or event-related power spectrum perturbation (ERPSP) is performed before the subject is exposed to the stimulus and every time after the subject is exposed to the stimulus. In both cases it is estimated in different regions of the brain.
脳の複数領域に於けるＥＲＰ時間領域成分の刺激前と刺激後の差分及び目的と紛乱（ｔａｒｇｅｔ ａｎｄ ｄｉｓｔｒａｃｔｅｒ）の差分の計測が決定される（ＤＥＲＰ）。テータ、アルファ、ベータ、ガンマ、及び高ガンマを含み、それに限定されない複数の周波数帯に亘り注意力、感情用務、及び記憶保持を推定する差分応答（ＤＥＲＰＳＰ）のイベント関係時間−周波数解析が実施される。特種の実施例に於いては、共鳴尺度の向上のため、単一の試行及び／或は平均ＤＥＲＰ及び／或はＤＥＲＰＳＰを使用することが出来る。 The measurement of the difference between the pre-stimulation and post-stimulation of the ERP time domain component and the difference between the target and the distracter in a plurality of brain regions (DERP) is determined. A differential response (DERPSP) event-related time- frequency analysis is performed that estimates attention, emotional service, and memory retention across multiple frequency bands including, but not limited to, data, alpha, beta, gamma, and high gamma. The In particular embodiments, a single trial and / or average DERP and / or DERPSP can be used to improve the resonance scale.
消費者経験査定は実物／関係に関連する刺激の区分の脳領域可干渉性尺度、ＥＥＧ計測の時間−周波数解析を含む神経生理学的尺度に基づく注意力、感情用務及び記憶保持推定を合成する区分効率尺度、及び非連結相互作用を有する区分と比較して連結／関係パタンが出現する区分期間の差分衝撃運動に関連する神経的尺度を使用する関係査定を更に編入してもよい。 Consumer experience assessment is a category that synthesizes attentional, emotional services and memory retention estimates based on neurophysiological measures, including brain region coherence measures of real / relationship-related stimulus categories, time- frequency analysis of EEG measurements A relational assessment may be further incorporated that uses an efficiency measure and a neural measure related to differential impact motion during a segmental period in which a connected / related pattern appears compared to a segment with unconnected interactions.
種々の実施例に於いて、消費者経験査定システムは対象／個人の組み分け可能性を引き出すために、人為行為の有無を問わず自動的のシステムを含むことが出来る。例えば、これにはパタン認知及び対象特定のテクニクが含まれる。これらサブシステムにはハードウエア実施及び／或はソフトウエア実施が含まれてもよい。 In various embodiments, the consumer experience assessment system can include an automated system with or without human activity to derive subject / individual grouping possibilities. For example, this includes pattern recognition and target specific techniques. These subsystems may include hardware implementations and / or software implementations.
エンタテインメント及びマーケティング材料、メディアストリーム、広告板、印刷広告、テキストストリーム、音楽、上演、感覚的経験などの種々の刺激材料が解析され得る。種々の実施例に於いて、モダリティ間（ｃｒｏｓｓ−ｍｏｄａｌｉｔｙ）測定機構向上とモダリティ内（ｉｎｔｒａ−ｍｏｄａｌｉｔｙ）測定向上の両方を実施するデータ解析装置を使用することによって向上された神経応答データが生成される。種々の実施例に於いて、活性のある領域を決定するためのみならず、異なる領域間の相互作用及び作用のタイプを決定するために脳活動が測定される。本発明のテクニク及び機構に於いては、神経的部位間の反応が入念に準備されて組織化された動作を支持するものであると認識されて居る。注意力、感情、記憶、及びその他の能力は単に脳の一部分によるものでなく、脳部位間のネットワーク反応によるものである。 Various stimulating materials such as entertainment and marketing materials, media streams, billboards, printed advertisements, text streams, music, performances, sensory experiences, etc. can be analyzed. In various embodiments, improved neural response data is generated by using a data analyzer that performs both cross-modality measurement mechanism improvement and intra-modality measurement improvement. The In various embodiments, brain activity is measured not only to determine active areas, but also to determine interactions and types of action between different areas. In the techniques and mechanisms of the present invention, it is recognized that reactions between neural sites support carefully prepared and organized movements. Attention, emotion, memory, and other abilities are not simply due to parts of the brain, but are due to network reactions between brain regions.
本発明のテクニク及び機構に於いては更に、複数の部位の間の交信に使用される異なる周波数帯が刺激の効率を示すもとであると認識されて居る。特種な実施例に於いて、推定に当って各被験者は目盛調整が行われ、被験者全体が同時化される。また、特種な実施例に於いて、刺激前後の差分の計測のためのベースラインを生成するために被験者用のテンプレイトが作成される。種々の実施例に於いて、刺激生成装置は情報処理機能を有するもの（ｉｎｔｅｌｌｉｇｅｎｔ）であり、露出時間とか、各被験者が解析される時間長などの特定のパラメタを適応的に変化させるものである。 In the technique and mechanism of the present invention, it is further recognized that the different frequency bands used for communication between multiple sites indicate the efficiency of stimulation. In a particular embodiment, each subject is calibrated for estimation and the entire subject is synchronized. In a special embodiment, a template for a subject is created to generate a baseline for measuring the difference before and after the stimulus. In various embodiments, the stimulus generator is intelligent and adaptively changes certain parameters such as exposure time and the length of time each subject is analyzed. .
ＥＥＧ、ＧＳＲ、ＥＫＧ、瞳孔拡張、ＥＯＧ、眼球追跡、顔面感情記号化、反応時間など、種々なモダリティが使用され得る。ＥＥＧのような個々の形態は、神経部位交信通路を情報処理機能をもって認識することによって向上される。モダリティ間解析は、中枢神経系統、自律神経系統、及び作動体の特徴の合成と解析的混合によって向上することが出来る種々の時間及び位相変化、相互関係及びモダリティ内決定のような機構による合成及び解析によって、効率よく消費者経験査定を実施するように各種のデータ応答の意義を特徴付ける合成出力を生成することが出来る。 Various modalities may be used such as EEG, GSR, EKG, pupil dilation, EOG, eye tracking, facial emotion symbolization, reaction time, etc. Individual forms such as EEG are improved by recognizing the nerve site communication path with an information processing function. Intermodality analysis can be enhanced by synthesizing and analytically mixing the characteristics of the central nervous system, autonomic nervous system, and actuators with mechanisms such as various time and phase changes, interrelationships, and intramodality decisions. The analysis can generate a composite output that characterizes the significance of various data responses so that a consumer experience assessment can be conducted efficiently.
図１は中枢神経系統、自律神経系統、及び／或は作動体測定を使用して消費者経験査定を実施するシステムの一例を示すものである。種々の実施例に於いて、消費者経験査定システムは刺激提出装置１０１を含む。特種な実施例の場合、刺激提出装置１０１は使用者に刺激材料を示す単なる陳列、モニタ、画面などである。刺激材料とはメディアクリップ、広告放送、文書の頁、ブランド画像、演技、雑誌広告、映画、オーディオ上演、などであり、特種な味、匂い、手触り及び／或は音などが含まれてもよい。刺激は種々の感覚に関するものであってよく、人的監督の如何に関係しない。他の例に於いて、刺激提出には使用者への製品、サービス、提出物或は経験の提供が含まれもよい。連続的なもの、不連続的なもの、両方が含まれる。種々の実施例に於いて、刺激提出装置１０１は、異なるある市場に於ける複数の被験者に与えられる刺激を特注生産出来るようなプロトコル生成の機能も有する。 FIG. 1 illustrates an example of a system that performs consumer experience assessment using central nervous system, autonomic nervous system, and / or actuator measurements. In various embodiments, the consumer experience assessment system includes a stimulus submission device 101. In a particular embodiment, the stimulus submission device 101 is simply a display, monitor, screen, etc. that shows the stimulus material to the user. Stimulus materials are media clips, advertisement broadcasts, document pages, brand images, performances, magazine advertisements, movies, audio performances, etc., and may include special tastes, smells, touches and / or sounds. . The stimulus may be related to various sensations and is not related to human supervision. In other examples, stimulus submission may include providing products, services, submissions or experiences to the user. Both continuous and discontinuous are included. In various embodiments, the stimulus submission device 101 also has the ability to generate a protocol that allows custom production of stimuli to be given to multiple subjects in different markets.
種々の実施例に於いて、刺激提出装置１０１には異なるネットワーク、ローカルネットワーク、ケーブルチャンネル、連合企業源、ウエブサイト、インタネット内容集成装置、ポータル、サービス企業などからの広告やエンタテインメントを含み、それに制限されない刺激を呈上するためのテレビジョン、ケーブルコンソル、コンピュータ及びモニタ、投影システム、ディスプレイ装置、スピーカ、触覚面などを含むことが出来る。 In various embodiments, the stimulus submission device 101 includes, and is limited to, advertisements and entertainment from different networks, local networks, cable channels, federated corporate sources, websites, internet content aggregation devices, portals, service companies, etc. Televisions, cable consoles, computers and monitors, projection systems, display devices, speakers, tactile surfaces, etc. for presenting unstimulated stimuli can be included.
種々の実施例に於いて、被験者はデータ収集装置１０５に接続される。このデータ収集装置１０５は、ＥＥＧ、ＥＯＧ、ＧＳＲ、ＥＫＧ、瞳孔拡張、眼球追跡、顔面感情記号化、反応時間装置など各種の神経学的及び神経生理学的測定機構を含む各種の神経応答測定機構を含んでも良い。種々の実施例に於いて、神経応答データには中枢神経系システム、自律神経系システム、及び作動体データが含まれる。特種な実施例に於いて、データ収集装置１０５は、ＥＥＧ１１１、ＥＯＧ１１３、ＧＳＲ１１５を有して居る。場合によっては、只一個のデータ収集装置が使用される。データの収集には人的監督があっても、なくても良い。
In various embodiments, the subject is connected to the
データ収集装置１０５は複数個の源から神経生理学的データを収集する。これには中枢神経系統源（ＥＥＧ）、自律神経系統源（ＧＳＲ，ＥＫＧ、瞳孔拡張）、及び作動体源（ＥＯＧ、眼球追跡、顔面感情記号化、反応時間）が含まれる。特定の実施例に於いて、収集されたデータはデジタルにサンプリングされ、後段の解析に保存される。特定の実施例に於いて、収集されたデータはリアルタイムに解析されることも出来る。特種な実施例に於いて、ディジタルサンプリングの速度は測定されて居る神経学的及び神経生理学的データに基づいて適応的に選択される。
特種な一実施例に於いて、消費者経験査定システムは頭皮レベル電極を使用して行うＥＥＧ１１１計測、目のデータを追跡する遮蔽電極を使用して行うＥＯＧ１１３計測、差分計測システムを使用して行うＧＳＲ１１５計測、顔の上の特定の箇所に設置された遮蔽電極による顔面筋肉計測、及び個人別に適応的に得られた顔面作用画面及びビデオ解析装置を含むものである。 In one particular embodiment, the consumer experience assessment system uses an EEG 111 measurement performed using a scalp level electrode, an EOG 113 measurement performed using a shielding electrode that tracks eye data, and a differential measurement system. It includes GSR115 measurement, facial muscle measurement with shielding electrodes installed at specific locations on the face, and facial action screens and video analysis devices obtained adaptively for each individual.
特種な実施例に於いて、データ収集装置はプロトコル生成及び提出装置１０１と同期化されたクロックである。特種な実施例に於いて、データ収集装置１０５は更にデータの収集につれて連続的に被験者の状態を監視する自動的トリガ、警告、及び状態監視可視化部品を提供する状態推定サブシステム、及びデータ収集用具を含む。この状態推定サブシステムは更に可視警告を提供し、自動的に矯正行為のトリガとなるものでもよい。種々の実施例に於いて、データ収集装置は被験者の刺激材料に対する神経応答を監視する機構を含むのみならず、刺激材料を特定したり監視したりする機構をも含むものである。例えばデータ収集装置１０５はチャンネルの変更を監視するセットトップボクス(ｓｅｔ−ｔｏｐ ｂｏｘ）と同期されて居ても良い。別の例として、データ収集装置１０５は被験者が刺激材料に注意を払わなくなった時にモニタと方向的に同期されてもよい。更に異なる例として、データ収集装置１０５は刺激がプログラム、広告放送、印刷物、経験、或は窓からの景色であるかに拘らず、一般的に被験者に観察される刺激材料を受けて保存するものでもよい。収集されたデータにより、神経応答情報、及び情報と単に被験者が気をそらして居るものでなく実際の刺激材料の情報との相関性の解析が可能となる。
In a particular embodiment, the data collection device is a clock synchronized with the protocol generation and submission device 101. In particular embodiments, the
種々の実施例に於いて、共鳴推定システムはデータ洗浄装置１２１をも含むものである。特種な実施例に於いて、このデータ洗浄装置１２１とは収集されたデータを濾過して、固定或は適応的濾過、加重平均法、高等成分抽出（例えばＰＣＡ，ＩＣＡ）、ベクトル及び成分分離法などにより、ノイズ、アーチファクト、及びその他の無用なデータを除去するものである。この装置は外因性のノイズ（原因が被験者の生理以外の場合）も内因性のアーチファクト（原因が筋肉運動、目の瞬きなどのような神経整理学的なものである場合）も除去することによってデータを洗浄するものである。 In various embodiments, the resonance estimation system also includes a data cleaning device 121. In a particular embodiment, the data cleaning device 121 filters the collected data to provide a fixed or adaptive filtration, weighted average method, higher component extraction (eg, PCA, ICA), vector and component separation method. For example, noise, artifacts, and other unnecessary data are removed. The device removes both extrinsic noise (if the cause is other than the subject's physiology) as well as intrinsic artifacts (if the cause is neuro-organized such as muscle movement, blinking of the eyes, etc.) The data is to be washed.
アーチファクト除去サブシステムは、応答データを選択的に分離して検査し、線周波数、目の瞬き、及び筋肉運動のようなアーチファクトに対応する時間区域及び／或は周波数領域特質で時代（ｅｐｏｃｈ）を特定する機構を含むものである。そうして、アーチファクト除去サブシステムは、これらの時代を除き、或はこれらの時代のデータをその他のクリーンなデータ（例えばＥＥＧの最隣接による加重平均方法）による予想値で置き換えて、アーチファクトを洗浄するものである。 The artifact removal subsystem selectively isolates and examines the response data and epochs with time zones and / or frequency domain characteristics corresponding to artifacts such as line frequency , blinking of the eye, and muscle movement. Includes a mechanism to identify. The artifact removal subsystem then removes these eras or replaces these era data with the expected values from other clean data (eg, weighted average method with EEG nearest neighbors) to clean up artifacts. To do.
種々の実施例に於いて、データ洗浄装置１２１はハードウエア、ファームウエア、及び／或はソフトウエアを使用して実現し得る。データ洗浄装置１２１はデータ収集装置１０５の後でデータ解析装置１８１の前の位置に示されて居るが、その他の装置と同様に、データ洗浄装置１２１はシステムの実施に基づいた位置及び機能を持つことが出来ると理解すべきものである。例えば、システムによっては自動的データ洗浄装置を全然使用しなくてもよい。その一方、その他のシステムに於いては、データ洗浄装置が個別のデータ収集装置に組み込まれて居てもよい。
In various embodiments, the data cleaning device 121 may be implemented using hardware, firmware, and / or software. Although the data cleaning device 121 is shown in a position after the
種々の実施例に於いて、複数の被験者に呈示される刺激材料に関する情報が任意の刺激属性貯蔵装置１３１で提供される。種々の実施例に於いて、刺激属性には目的、呈示属性、報告生成属性などと共に刺激材料の特徴も含まれる。特種の実施例に於いて、刺激属性には時間的期間、チャンネル、推定、メディア、タイプ、その他が含まれる。刺激属性には更に種々の枠内の物体の位置、成分、イベント，対象間関係、対象の位置、陳列持続期間が含まれても良い。目的属性には抱負，及び興奮、記憶保持、連想、その他を含む刺激の対象が含まれる。呈示属性にはオーディオ、ビデオ、形象、及び強化或は回避に必要なメッセージが含まれる。その他の属性は刺激属性貯蔵装置或はその他の貯蔵装置に含まれても含まれなくても良い。 In various embodiments, information regarding the stimulus material presented to multiple subjects is provided in the optional stimulus attribute store 131. In various embodiments, stimulus attributes include features of the stimulus material as well as purpose, presentation attributes, report generation attributes, and the like. In particular embodiments, stimulus attributes include time duration, channel, estimation, media, type, etc. The stimulus attribute may further include the position, component, event, inter-object relationship, target position, and display duration of the object in various frames. Objective attributes include aspirations and stimuli, including excitement, memory retention, association, and others. Presentation attributes include audio, video, shapes, and messages required for enhancement or avoidance. Other attributes may or may not be included in the stimulus attribute storage device or other storage device.
データ洗浄装置１２１と刺激属性貯蔵装置１３１とはデータ解析装置１８１にデータを通す。データ解析装置１８１は各種の機構を使用してシステム中の基礎をなすデータを解析し、消費者経験を決定する。種々の実施例に於いて、データ解析装置は各モダリティの個人毎に独立の神経学的及び神経生理学的パラメタをカストマイズして抽出し、モダリティ間のみならずモダリティ内の推定を混合して提出された刺激への向上された応答を引き出すように構成されて居る。特種の実施例に於いて、データ解析装置１８１はデータセット内の異なる被験者に亘る応答データを集成する。 The data cleaning device 121 and the stimulus attribute storage device 131 pass data to the data analysis device 181. Data analyzer 181 uses various mechanisms to analyze the underlying data in the system to determine consumer experience. In various embodiments, the data analysis device can customize and extract independent neurological and neurophysiological parameters for each modality individual, and submit a mix of estimates within the modality as well as between modalities. It is configured to elicit an improved response to irritating stimuli. In a particular embodiment, the data analyzer 181 aggregates response data across different subjects in the data set.
種々の実施例に於いて、神経学的及び神経生理学的特徴は時間域解析及び周波数ドメイン解析を使用して測定される。これらの解析には、各個人に独特のパラメタのみならず、個人間に共通のパラメタも使用される。解析には統計パラメタ抽出及び合成された応答の時間及び周波数成分両方からのファジイロジックに基づく属性推定も含むことが出来る。 In various embodiments, neurological and neurophysiological features are measured using time domain analysis and frequency domain analysis. These analyzes use not only parameters that are unique to each individual, but also parameters that are common among individuals. The analysis can also include statistical parameter extraction and attribute estimation based on fuzzy logic from both the time and frequency components of the synthesized response.
或る例に於いては、融合された効率推定に使用される統計パラメタに、注意力、感情用務及び記憶保持のファジイ推定のみならず、歪み，頂点，第一及び第二モーメント、人口分布が含まれる。 In some examples, the statistical parameters used in the integrated efficiency estimation include not only fuzzy estimates of attention, emotional affairs, and memory retention, but also distortion, vertices, first and second moments, and population distribution. included.
種々の実施例に於いて、データ解析装置１８１はモダリティ内応答合成装置及びモダリティ間応答合成装置を含んでもよい。特種実施例に於いて、モダリティ内応答合成装置は各モダリティの各個人用に独立した神経学的及び神経生理学的パラメタをカストマイズして抽出し、モダリティ内の推定を解析的に混合して呈上された刺激への向上された応答を引き出すように構成されて居る。特種実施例に於いて、モダリティ内応答合成装置は更にデータセット内の異なる被験者からのデータを集成する。 In various embodiments, the data analyzer 181 may include an intra-modality response synthesizer and an inter-modality response synthesizer. In the specific embodiment, the intra-modality response synthesizer customizes and extracts independent neurological and neurophysiological parameters for each individual of each modality, and presents the estimation within the modality mixed analytically. Configured to elicit an improved response to the stimulated stimulus. In a specific embodiment, the intra-modality response synthesizer further aggregates data from different subjects in the data set.
種々の実施例に於いて、モダリティ間応答合成装置或は融合装置は未加工信号及び信号出力を含む異なるモダリティ間応答を融合する。信号の結合はモダリティ内での効率の尺度を向上する。モダリティ間応答融合装置は更にデータセット内の異なる被験者からのデータを集成することが出来る。 In various embodiments, the inter-modality response synthesizer or fusion device fuses different inter-modality responses including raw signals and signal outputs. Signal combining improves the efficiency measure within the modality. The inter-modality response fusion device can also aggregate data from different subjects in the data set.
種々の実施例に於いて、データ解析装置１８１は各モダリティからの向上された応答や推定を結合し各種の目的の為の効率の混合推定を提出する合成向上効率推定装置（ＣＥＥＥ＝ｃｏｍｐｏｓｉｔｅ ｅｎｈａｎｃｅｄ ｅｆｆｅｃｔｉｖｅｎｅｓｓ ｅｓｔｉｍａｔｏｒ）を更に含むものである。特種例に於いて、混合推定は被験者の刺激材料への露出ごとに与えられる。混合推定は時間をかけて推定され、消費者経験の特徴が査定される。種々の実施例に於いて、混合推定の各々には数値が割り当てられる。これらの数値は神経応答の強度、頂点の意義、頂点間の変更などに対応するものでもよい。高い数値が神経応答の強度に於ける意義の高いことに対応するものであってもよい。低い数値は神経応答の意義が低いこと、或いは神経応答活動が無意義であることに対応するもであってもよい。更に別の例として、神経応答意義の混合推定は露出が繰り返された後の変化を示すためにグラフとして示される。 In various embodiments, the data analyzer 181 combines improved responses and estimates from each modality and submits a combined enhanced efficiency estimator (CEEE = composite enhanced effectivity) that submits a mixed estimate of efficiency for various purposes. estimator). In a special case, a mixture estimate is given for each exposure of the subject to the stimulus material. Mixture estimates are estimated over time and consumer experience characteristics are assessed. In various embodiments, each of the mixture estimates is assigned a numerical value. These numbers may correspond to the strength of the neural response, the significance of the vertices, changes between vertices, and the like. A high number may correspond to a high significance in the strength of the neural response. A low number may correspond to a low significance of neural response or a non-significant neural response activity. As yet another example, a mixed estimate of neural response significance is shown as a graph to show changes after repeated exposures.
種々の実施例に於いて、データ解析装置１８１は解析され向上された応答データをデータ通信装置１８３に供給する。特種の場合に於いてはデータ通信装置１８３が不要である点に注意されたい。種々の実施例に於いて、データ通信装置１８３は未加工及び／或は解析後データ及び洞察結果を供給する。特種の実施例として、データ通信装置１８３は貯蔵と交信の保障のためにデータを圧縮及びコード化する機構を含んでも良い。 In various embodiments, the data analysis device 181 provides response data that has been analyzed and improved to the data communication device 183. It should be noted that the data communication device 183 is unnecessary in special cases. In various embodiments, the data communication device 183 provides raw and / or post-analysis data and insight results. As a specific embodiment, the data communication device 183 may include a mechanism for compressing and encoding data for storage and communication security.
種々の実施例に於いて、データ通信装置１８３は種々の従来のバス、有線ネットワーク、無線ネットワーク、衛星及び専売通信プロトコルのみならず、ファイル転送プロトコル（ＦＴＰ），ハイパテキスト転送プロトコル（ＨＴＴＰ）のようなプロトコルを使用してデータを送信する。送信されるデータには、データ全部、部分データ、転換データ、及び／或は引き出された応答尺度が含まれてもよい。種々の実施例に於いて、データ通信装置はデータ収集装置から応答統合装置１８５に得られたデータを送信するセットトップボクス、無線装置、コンピュータシステムなどである。特種例に於いて、データ通信装置はデータ洗浄或いはデータ解析以前にデータを送信してもよい。その他の例に於いて、データ通信装置はデータ洗浄或いはデータ解析の後にデータを送信してもよい。 In various embodiments, the data communication device 183 includes various conventional buses, wired networks, wireless networks, satellites and proprietary communication protocols as well as file transfer protocol (FTP) and hypertext transfer protocol (HTTP). Send data using any protocol. The transmitted data may include full data, partial data, conversion data, and / or derived response measures. In various embodiments, the data communication device is a set-top box, wireless device, computer system, etc. that transmits data obtained from the data collection device to the response integration device 185. In a specific example, the data communication device may transmit data before data cleaning or data analysis. In other examples, the data communication device may transmit data after data cleaning or data analysis.
特種の実施例に於いて、データ通信装置１８３は応答統合システム１８５にデータを送信する。種々の実施例に於いて、応答統合システム１８５は消費者経験パタンにアクセスしてそれを抽出する。特種の実施例に於いて、応答統合システム１８５は種々の刺激区分の中に於いて実***置を決定し、衝動性運動を注意力、記憶保持、感情用務の神経的評価と相関させながら位置情報を眼球追跡軌跡と照合する。特種の実施例の場合、応答統合システム１８５は更に使用者の行為を収集して統合し、応答を解析した応答を査定して消費者経験をより効率的に推定する。 In a particular embodiment, the data communication device 183 transmits data to the response integration system 185. In various embodiments, the response integration system 185 accesses and extracts consumer experience patterns. In a particular embodiment, the response integration system 185 determines the location of the substance in various stimulus categories and correlates the impulsive movement with the neural assessment of attention, memory retention, and emotional services. Is matched with the eye tracking trajectory. In the specific embodiment, the response integration system 185 further collects and integrates user actions and assesses the responses analyzed to more efficiently estimate consumer experience.
爾後の解析、管理、取り扱い及び検索のために、各種のデータを貯蔵することが出来る。特種の実施例に於いて、貯蔵装置は刺激属性、呈示属性、聴衆応答の追跡のため、また任意的に聴衆計測情報を統合するために使用することが出来る。 Various data can be stored for later analysis, management, handling and retrieval. In particular embodiments, the storage device can be used to track stimulus attributes, presentation attributes, audience responses, and optionally to integrate audience measurement information.
システムの中の各種の部品の場合と同様、応答統合はシステムのその他の部分及び使用者と共に位置されてもよく、遠隔地に実施されてもよい。又任意的に、集中されてよく、供給者或いは刺激材料の供給者に分布されてもよい査定貯蔵システムの中へと分離されてもよい。その他の実施例に於いて、応答統合システムは刺激材料供給者及び／或は使用者にとって接触可能な第三者であるサービス提供者の施設に収容される。 As with the various components in the system, response integration may be located with other parts of the system and the user, or may be performed remotely. Also optionally, it may be centralized and separated into an assessment storage system that may be distributed to suppliers or suppliers of stimulating materials. In other embodiments, the response integration system is housed in a third party service provider's facility accessible to the stimulus material supplier and / or user.
図２は刺激属性貯蔵装置を供給されたデータモデルの例を示すものである。種々の実施例に於いて、刺激属性データモデル２０１はチャンネル２０３、メディアタイプ２０５、時間間隔２０７、聴衆２０９、及び人口統計学的情報２１１を含む。刺激目的データモデル２１５は意図２１７及び目標２１９を含んでもよい。種々の実施例に於いて、刺激属性データモデル２０１は更に経験の中の種々の時間的、空間的、活動、及びイベント成分に関する成分情報を含む。
FIG. 2 shows an example of a data model supplied with a stimulus attribute storage device. In various embodiments, the stimulus attribute data model 201 includes a channel 203, a media type 205, a
種々の実施例に於いて、別の刺激属性データモデル２２２は創造属性２２３、所有権属性２２５、放送属性２２７、及び統計的、人口統計的、及び／或は神経生理学的及び神経行為的応答を刺激に関係するその他の属性及びメタ情報（ｍｅｔａ−ｉｎｆｏｒｍａｔｉｏｎ）を自動的に統合する査定に基づく識別子を含む。 In various embodiments, another stimulus attribute data model 222 includes creative attributes 223, ownership attributes 225, broadcast attributes 227, and statistical, demographic, and / or neurophysiological and neuroactive responses. Includes assessment-based identifiers that automatically integrate other attributes related to stimuli and meta-information.
図３は消費者経験の追跡及び測定に関する情報の貯蔵に使用され得るデータモデルの例を示す。種々の実施例に於いて、データセットデータモデル３０１は実験名３０３及び／或は識別子、顧客属性３０５、被験者群３０７、テストの位置、日付、時間のようなロジスティクス情報３０９、及び刺激材料属性を含む刺激材料３１１を含む。
FIG. 3 shows an example of a data model that can be used to store information related to tracking and measuring consumer experience. In various embodiments, the dataset data model 301 includes experiment names 303 and / or identifiers, customer attributes 305,
特種の実施例に於いて、刺激属性データモデル３１５は被験者名３１７及び／或は識別子、コンタクト情報３２１、及び神経学的及び神経生理学的データの検査に便利となり得る人口統計学的属性３１９を含む。関係のある人口統計学的属性の例には結婚状態、就職状態、職業、家族の収入、家族のサイズ及び構成、民族性、地理的位置、性別、人種がある。その他の分野でデータモデル３１５に含まれてよいものには、ショッピングに関する選択、エンタテインメントに関する選択、及び財政に関する選択がある。ショッピングに関する選択には、好みの店舗、ショッピングの頻度、購買のカテゴリ、好みのブランドがある。エンタテインメントに関する選択には、ネットワーク／ケーブル／衛星放送へのアクセス機能、気に入りの演劇、気に入りの種類、及び気に入りの俳優が含まれる。財政に関する選択には、気に入りの保険会社、選択される投資の実行、銀行に関する選択、及び気に入りのオンラインの財政手段が含まれる。刺激属性データモデル３１５には種々の被験者属性が含まれてよく、データモデルは事前設置でも、特種の目的に合わせて生成されてもよい。
In particular embodiments, stimulus attribute data model 315 includes
種々の実施例に於いて、神経フィードバック関連用データモデル３２５は実験プロトコル３２７、ＥＥＧ，ＥＯＧ，ＧＳＲのような含まれたモダリティ３２９、実施された査定、及び区分及び区分属性のような実験設計パラメタを特定する。その他の分野には実験呈示原稿、区分長さ、使用された刺激材料のような区分の詳細、被験者間の変動、被験者内の変動、指示、呈示順序、使用された調査質問などが含まれてもよい。その他のデータモデルにはデータ収集データモデル３３７が含まれてもよい。種々の実施例に於いて、データ収集データモデル３３７には局及び位置識別子のような記録属性３３９、記録のデータ及び時間、及び操作人に関する詳細が含まれる。種々の実施例に於いて、用具属性３４１には増幅器識別子及びセンサ識別子が含まれる。 In various embodiments, the neural feedback-related data model 325 includes experimental protocols 327, included modalities 329 such as EEG, EOG, GSR, performed assessments, and experimental design parameters such as category and category attributes. Is identified. Other areas include experimental presentation manuscripts, segment lengths, segment details such as stimulus material used, subject-to-subject variation, subject variation, instructions, presentation order, survey questions used, etc. Also good. Other data models may include a data collection data model 337. In various embodiments, the data collection data model 337 includes recording attributes 339 such as station and location identifiers, recording data and time, and details about the operator. In various embodiments, tool attributes 341 include an amplifier identifier and a sensor identifier.
記録モダリティ３４３にはＥＥＧキャップ設計、活性チャンネル、サンプリング周波数、及び使用フィルタのようなモダリティ特有属性が含まれてもよい。ＥＯＧに特有の属性には使用されるセンサの数と種類、設置されたセンサの位置などが含まれる。眼球追跡に特有な属性には使用された追跡用具の種類、データの記録頻度、記録されて居るデータ、記録様式などが含まれる。種々の実施例に於いて、データ貯蔵属性３４５にはファイル貯蔵慣例（様式、名付け慣例、日付慣例）、貯蔵位置、アーカイブ属性、満期属性などが含まれる。 The recording modality 343 may include modality specific attributes such as EEG cap design, active channel, sampling frequency , and used filter. Attributes unique to EOG include the number and type of sensors used, the location of installed sensors, and the like. Attributes specific to eye tracking include the type of tracking tool used, the frequency of data recording, the data being recorded, the recording format, and the like. In various embodiments, data storage attributes 345 include file storage conventions (style, naming convention, date convention), storage location, archive attributes, maturity attributes, and the like.
既成質問データモデル３４９は、質問名３５１及び／或は識別子、関係するデータ区分（モデル、データベース／キューブ、表など）のようなアクセスされたデータ群３５３、誰がどのようなタイプのアクセスを持つかを含むアクセス安全属性３５５、及び質問の満期のようなリフレッシュ属性３５７、リフレッシュ頻度などを含む。その他、プルプッシュ選択（ｐｕｌｌ−ｐｕｓｈ ｐｒｅｆｅｒｅｎｃｅ）のような分野も、自動プッシュ報告ドライバ或は使用者駆動の報告検索システムを特定するために含まれてよい。
The pre-built question data model 349 is a group of accessed data 353, such as a
図４は消費者経験査定に関するデータ獲得のために実施され得る質問の例を示すものである。例えば、使用者は或る特定の経験或は経験の成分に対してどのような消費者がもっとも反応するものか決定するために質問をしてもよい。種々の実施例に於いて、質問とは一般的或はカストマイズされた手書き言語及び構成、視覚的構成、既定質問の蔵書、ドリルダウン診断を含む診断的質問、及びシナリオであったらそれを引き出すことから定義されるものである。種々の実施例によれば、被験者特性質問４１５は、位置４１７或は地理的情報、試験時刻と日付のような活動期間情報、及び人口統計属性４１９などを使用してデータを神経情報貯蔵装置から取得するように構成されたものでもよい。人口統計属性には、家族収入、家族の人数及び地位、教育程度、子供の年齢などが含まれる。 FIG. 4 shows an example of a question that can be conducted to obtain data on consumer experience assessment. For example, the user may ask questions to determine what consumers are most responsive to a particular experience or component of experience. In various embodiments, a question is a generic or customized handwritten language and composition, a visual composition, a collection of default questions, a diagnostic question including drill-down diagnostics, and a scenario to derive it Is defined by According to various embodiments, subject characteristic query 415 may retrieve data from neural information store using location 417 or geographic information, activity period information such as test time and date, demographic attributes 419, and the like. It may be configured to obtain. Demographic attributes include family income, number and status of family members, degree of education, age of children, and the like.
その他の質問は、関係被験者の購買選択、支持、生理的査定、完成状態に基づいて刺激材料を検索するものであってもよい。例えば、使用者は製品カテゴリ、購入された製品、頻繁に購買する商店、被験者の眼修正状態、色盲、被験者状態、測定応答の信号強度、アルファ周波数バンドリンガ（ｂａｎｄ ｒｉｎｇｅｒ）、筋肉動作査定、完成セグメントなどに関係するデータについて質問してもよい。実験的デザインに基づいた質問によって、神経情報貯蔵装置から、実験的プロトコル４２７、製品カテゴリ４２９、含まれた調査４３１、及び供給された刺激４３３に基づいたデータが得られるかもしれない。その他、使用されたプロトコルの繰り返し数、使用されたプロトコルの結合、及び調査の使用構成のような分野も使用出来よう。 Other questions may be to search for stimulating material based on purchase selection, support, physiological assessment, and completion status of relevant subjects. For example, a user may have a product category, a purchased product, a frequently purchased store, a subject's eye correction status, color blindness, subject status, measurement response signal strength, alpha frequency band ringer, muscle motion assessment, completion You may ask about data related to segments. Questions based on experimental design may result in data from the neural information storage device based on experimental protocol 427, product category 429, included research 431, and delivered stimulus 433. Other areas such as the number of protocol repetitions used, the combination of protocols used, and the usage configuration of the survey could be used.
クライエント及び産業に基づいた質問によっては、テスティングに含まれた産業のタイプ、テストされた特種なカテゴリ、関係したクライエントの会社、及びテストされたブランドに基づいたデータが得られるかもしれない。質問に基づいた応答査定４３７には、集中力採点４３９、感情採点４４１、保持力採点４４３、及び効果力採点４４５が含まれてもよい。これらの質問によって、特種な採点を引き出す材料が得られるかも知れない。
Client and industry-based questions may provide data based on the type of industry included in the testing, the particular category tested, the company of the client involved, and the brand tested. . The response assessment 437 based on the question may include a
応答測定プロファイルに基づいた質問は、平均測定閾値、分散度、検出された頂点の数などを使用するものでもよい。グループ応答質問には、平均、分散、尖度、p値などのグループ統計、グループサイズ、異常値査定度などが含まれてもよい。更に別の質問には、テスト位置、テスト期間、テスト繰返し回数、テストステイション、及びテスト操作者フィールドのような試験特性が関係してもよい。効率よくデータを抽出するために、質問の各種の結合やタイプが使用されてよい。 The question based on the response measurement profile may use an average measurement threshold, a degree of dispersion, the number of detected vertices, and the like. Group response questions may include group statistics such as mean, variance, kurtosis, p-value, group size, outlier rating, etc. Still other questions may involve test characteristics such as test location, test duration, number of test repetitions, test station, and test operator field. Various combinations and types of questions may be used to extract data efficiently.
図５は、生成され得る報告の例を示すものである。種々の実施例に於いて、クライエント査定概略報告５０１には、効率尺度５０３、成分査定尺度５０５、及び消費者経験尺度５０７が含まれる。効率査定尺度には、合成査定尺度、産業／カテゴリ／クライエントに独特な配置（百分比、等級など）、材料除去、区分の変更、或は特種要素の最終的調整のような作用的グルーピング査定、及び効率プロファイルの時間的変化などが含まれる。特種な実施例に於いて、報告には材料の査定回数、使用された複数呈示の属性、複数呈示に亘る応答査定尺度の進化、及び使用推薦などが含まれる。 FIG. 5 shows an example of a report that can be generated. In various embodiments, the client assessment summary report 501 includes an efficiency measure 503, a component assessment measure 505, and a consumer experience measure 507. Efficiency assessment scales include synthetic assessment scales, industry / category / client-specific placement (percentage, grade, etc.), active grouping assessments such as material removal, segmentation changes, or final adjustments of specific elements, And changes in the efficiency profile over time. In particular embodiments, the report includes the number of material assessments, the attributes of the multiple presentations used, the evolution of the response assessment scale across multiple presentations, and usage recommendations.
種々の実施例に於いて、クライエント累積報告５１１は、査定された総ての刺激のメディアグループ報告５１３、及び査定された刺激のキャンペーングループ報告５１７が含まれる。種々の実施例に於いて、産業累積的及び協調報告５２１は、集合査定応答尺度５２３、上位演技者リスト５２５、下位演技者リスト５２７、異常値５２９、及び流行報告５３１が含まれる。特種な実施例に於いては、追跡及び報告に、特種な製品、カテゴリ、会社、ブランドが含まれる。
In various embodiments, the client cumulative report 511 includes a media group report 513 of all assessed stimuli and a campaign group report 517 of assessed stimuli. In various embodiments, industry cumulative and
図６は消費者経験査定の一例を示す。６０１に於いて刺激材料が複数の地理的市場の複数人の被験者に与えられる。種々の実施例に於いて、刺激には放送テレビ、ケーブルテレビ、衛星などの機構を通じて供給されるビデオやオーディオが含まれる。別の例として、刺激には実際の物理的製品、サービス、相互作用，及び経験が含まれてもよい。６０３に於いて、被験者応答はＥＥＧ，ＥＲＰ，ＥＯＧ，ＧＳＲ，などのような各種のモダリティを使用して収集される。或る例に於いては、口頭及び筆答での応答も収集され、神経学的及び神経生理学的応答と共に関連付けられることが出来る。６０５に於いてデータはデータ洗浄装置を通過され、データの解釈を難しくする元となるノイズ及びアーチファクトが除去される。種々の実施例に於いて、データ洗浄装置は瞬きやその他の外因的／内因的アーチファクトに関するＥＥＧ電気活動を除去する。 FIG. 6 shows an example of consumer experience assessment. At 601, stimulating material is provided to multiple subjects in multiple geographic markets. In various embodiments, stimuli include video and audio supplied through mechanisms such as broadcast television, cable television, and satellite. As another example, stimuli may include actual physical products, services, interactions, and experiences. At 603, subject responses are collected using various modalities such as EEG, ERP, EOG, GSR, etc. In some examples, verbal and written responses can also be collected and associated with neurological and neurophysiological responses. At 605, the data is passed through a data scrubber to remove noise and artifacts that make it difficult to interpret the data. In various embodiments, the data cleaning device removes EEG electrical activity related to blinks and other extrinsic / intrinsic artifacts.
種々の実施例に於いて、データ解析が実施される。データ解析に於いては効率尺度の向上のためにモダリティ内応答合成とモダリティ間応答合成とを含んで良い。或る特種の場合に於いては、他の種類の合成を行わずに一種の合成を行ってもよいことを銘記すべきものである。その例として、モダリティ間応答合成を行うのにモダリティ内応答合成を行っても、行わなくてもよい。 In various embodiments, data analysis is performed. Data analysis may include intra-modality response synthesis and inter-modality response synthesis to improve efficiency measures. It should be noted that in certain special cases, one type of synthesis may be performed without performing other types of synthesis. As an example, intermodal response synthesis may or may not be performed to perform intermodal response synthesis.
データ解析を実施する為に、種々の機構が使用され得る。特種実施例によれば、目的、意図，目標などと共に刺激材料の属性及び特徴を獲得するために刺激属性貯蔵装置１３１が検索される。特種実施例に於いて、ＥＥＧ応答データが向上された効率検索を提供するために合成される。種々の実施例に於いて、ＥＥＧは脳の異なる部位に関係する何千もの同時的神経工程の結果である電気的活動を測定するものである。ＥＥＧデータは幾つかのバンド（帯）に分級することが出来るものであり、種々の実施例に於いて、脳波周波数はデルタ、テータ、アルファ、ベータ、及びガンマ周波数レンジを含むものである。デルタ波は４Ｈｚ以下のものであり、熟睡中に顕著なものである。テータ波は周期が３．５から７．５Ｈｚの間のものであり、記憶力、注意力、感情、及び感覚に関係する。テータ波は典型的に内的集中の時に顕著となる。 Various mechanisms can be used to perform data analysis. According to a special embodiment, the stimulus attribute storage device 131 is searched to obtain the attributes and features of the stimulus material along with the purpose, intention, goal, etc. In a specific embodiment, EEG response data is synthesized to provide an improved efficiency search. In various embodiments, EEG measures electrical activity that is the result of thousands of simultaneous neural processes involving different parts of the brain. EEG data can be classified into several bands, and in various embodiments, the electroencephalogram frequencies include delta, theta, alpha, beta, and gamma frequency ranges . The delta wave is below 4 Hz and is prominent during deep sleep. Theta waves have a period between 3.5 and 7.5 Hz and relate to memory, attention, emotion, and sensation. Theta waves are typically prominent during internal concentration.
アルファ周波数は７．５と１３Ｈｚの間であり、典型的に１０Ｈｚで頂上に達する。アルファ波は寛ぎの状態で顕著である。ベータ波の周波数レンジは１４から３０Ｈｚであり、ベータ波は運動制御、脳部位間の広範囲の同期、解析問題の解決、判断、決断などの期間に顕著である。ガンマ波は３０から６０Ｈｚの間に起こり、認知的或は運動機能及び注意力、記憶力の実行の為に異なるニューロン群をネットワークに結合することに関与するものである。頭蓋及び皮膚層はこの周波数範囲の波を減衰するため、７５−８０Ｈｚの範囲の脳波は検出が難しいため、刺激応答の評価には使用されないことが多い。 The alpha frequency is between 7.5 and 13 Hz, typically reaching the top at 10 Hz. Alpha waves are prominent in relaxation. The frequency range of the beta wave is 14 to 30 Hz, and the beta wave is prominent during periods such as motor control, wide-range synchronization between brain regions, solution of analysis problems, judgment, and decision. Gamma waves occur between 30 and 60 Hz and are involved in connecting different groups of neurons to the network for cognitive or motor function and attention and memory performance. Since the skull and skin layers attenuate waves in this frequency range, brain waves in the 75-80 Hz range are difficult to detect and are often not used to evaluate stimulus responses.
しかし、本発明のテクニクや機構に於いては、テータ、アルファ、ベータ、及び低ガンマ帯の計測に加えて高ガンマ帯（カッパ帯：６０Ｈｚ以上）の計測が神経学的注意力、感情用務、保持成分推定を向上することが認識されて居る。特種の実施例に於いて、取得するのが難しい高ガンマ或はカッパ帯測定をも含めたＥＥＧ測定が３０１に於いて取得され、向上され、評価される。テータ、アルファ、ベータ、ガンマ、及びカッパ帯での被験者及びタスクに合わせた部分帯が３０３で向上された応答推定のために特定される。種々の実施例に於いて、８０Ｈｚ以上の高ガンマ波（カッパ帯）（典型的に頭蓋下ＥＥＧ及び脳磁図によって検出可能）が刺激の周波応答の逆モデル基向上（ｉｎｖｅｒｓｅ ｍｏｄｅｌ−ｂａｓｅｄ ｅｎｈａｎｃｅｍｅｎｔ）に使用される。 However, in the technique and mechanism of the present invention, in addition to the measurement of theta, alpha, beta, and low gamma bands, the measurement of the high gamma band (kappa band: 60 Hz or more) can be used for neurological attention, emotional service, It has been recognized that the retention component estimation is improved. In a particular embodiment, EEG measurements, including high gamma or kappa band measurements, which are difficult to obtain, are obtained, enhanced and evaluated at 301. Subbands tailored to subjects and tasks in theta, alpha, beta, gamma, and kappa bands are identified for improved response estimation at 303. In various embodiments, high gamma waves (kappa bands) above 80 Hz (typically detectable by subcranial EEG and magnetoencephalography) can be used to inverse model-based enhancement of stimulus frequency response. used.
本発明の種々の実施例に於いて、或る活動の際、各周波数範囲の特定の部分帯が特に顕著になることが認知されて居る。特定の帯内の周波数の部分集合のことを此処では部分帯と呼称する。例えば、部分帯とはガンマ帯の中の４０−４５Ｈｚの範囲を含むものでもよい。特種の実施例に於いては、複数の部分帯が異なる帯から選択され、残りの周波は帯域通過濾過にかけられる。特種の実施例に於いては、複数の部分帯応答が向上され、残りの周波数応答が減衰される。 In various embodiments of the present invention, it has been recognized that certain sub-bands of each frequency range are particularly prominent during certain activities. A subset of frequencies within a particular band is referred to herein as a subband. For example, the partial band may include a range of 40-45 Hz in the gamma band. In a particular embodiment, the plurality of subbands are selected from different bands and the remaining frequencies are subjected to bandpass filtration. In particular embodiments, multiple subband responses are improved and the remaining frequency response is attenuated.
情報理論に基づくバンド調整モデルが、選択的データセット、被験者及びタスクに独特な帯の適応的抽出をして神経情報貯蔵データを向上すべく使用される。適応的抽出は、ファジイスケイリングを使用することで実施されてもよい。複数回に亘って刺激が提供され向上された測定が決定され、複数の呈上に亘っての変化プロファイルを決定することが出来る。変化プロファイルを決定することにより、一次的応答の向上応答ならびにマーケティング及びエンタテインメント刺激の長命（消耗）を提供することが出来る。複数の個人から協調的に提出される刺激への同期的応答が測定されて、被験者に亘る向上された効率の同期程度が提供される。種々の実施例に於いて、同期的応答は離れた位置に住む複数の被験者或は同じ地区に住む複数の被験者に対して決定されてよい。 Band theory models based on information theory are used to improve neural information storage data by adaptive sampling of bands specific to selective data sets, subjects and tasks. Adaptive extraction may be performed using fuzzy scaling. Stimulation is provided over multiple times, improved measurements are determined, and a change profile over multiple presentations can be determined. Determining the change profile can provide an enhanced response of primary response and a long life (depletion) of marketing and entertainment stimuli. Synchronous responses to stimuli submitted collaboratively from multiple individuals are measured to provide an improved degree of synchronized efficiency across subjects. In various embodiments, a synchronous response may be determined for multiple subjects living in remote locations or multiple subjects living in the same district.
種々の合成機構が記述されて居るが、機構間に於ける反応の有無に拘らず、何個の機構を順番的に、或は並列的に適応してもよいことを銘記すべきである。 Although various synthesis mechanisms have been described, it should be noted that any number of mechanisms may be applied in sequence or in parallel, with or without reaction between the mechanisms.
モダリティ内合成機構は向上された意味（ｓｉｇｎｉｆｉｃａｎｃｅ）データを供給するものであるが、追加的にモダリティ間合成機構も適応出来るものである。ＥＥＧ、眼球追跡、ＧＳＲ、ＥＯＧ，及び顔面運動符号化など各種の機構がモダリティ間合成機構に接続される。その他の機構及び現存の機構の変形及び向上品も含まれてよい。種々の実施例に於いて、特定のモダリティからのデータが一個以上の他のモダリティからのデータを使用して向上させられる。特種の実施例に於いては、ＥＥＧが典型的にアルファ、ベータ、及びガンマのような異なる帯でしばしば計測して、効率の推定を供給する。しかし、効率の計測価は他のモダリティからの情報を使用することによって更に向上し得るものであると言うことを、本発明のテクニクは認めるものである。 While the intra-modality synthesis mechanism provides improved semantic data, an inter-modality synthesis mechanism can additionally be adapted. Various mechanisms such as EEG, eye tracking, GSR, EOG, and facial motion coding are connected to the inter-modality synthesis mechanism. Other mechanisms and variations and enhancements of existing mechanisms may also be included. In various embodiments, data from a particular modality is enhanced using data from one or more other modalities. In particular embodiments, the EEG typically measures in different bands, such as alpha, beta, and gamma, to provide an estimate of efficiency. However, the technique of the present invention recognizes that the efficiency measure can be further improved by using information from other modalities.
例えば、顔面感情記号化はＥＥＧ感情用務特徴の数価を向上するのに使用可能である。対象実体のＥＯＧと眼球追跡衝動計測は、注意力、感情用務、及び記憶保持を含み且つそれに限定されない効率のＥＥＧ推定を向上させるのに使用可能である。種々の実施例に於いて、モダリティ間合成機構は異なるモダリティからのデータを整列させるようにデータの時間及び位相移動を行う。或る例に於いては、顔面感情測定が変化する数百ミリ秒前にＥＥＧ応答がしばしば起こることが認められて居る。相関性が得られ、時間及び位相移動がグループによってのみならず、個別にも行い得る。別の例に於いては、衝動的眼球運動を特定のＥＥＧ応答の前後に起こるものとして決定してもよい。種々の実施例に於いては、時間的に関連したＧＳＲ測定値が注意力、感情用務及び記憶保持測定を含む効率のＥＥＧ推定の規模変更及び向上に使用される。 For example, facial emotion symbolization can be used to improve the valence of EEG emotional service features. Target entity EOG and eye tracking impulse measurements can be used to improve EEG estimation of efficiency, including but not limited to attention, emotional affairs, and memory retention. In various embodiments, the inter-modality synthesis mechanism performs time and phase shifting of data to align data from different modalities. In some instances, it has been observed that EEG responses often occur hundreds of milliseconds before facial emotion measurements change. Correlation is obtained and time and phase shifts can be performed not only by group but also individually. In another example, impulsive eye movements may be determined as occurring before or after a particular EEG response. In various embodiments, temporally related GSR measurements are used to scale and improve EEG estimates of efficiency, including attention, emotional service, and memory retention measurements.
特定の部位での特定の時間領域差イベント関連電位成分（例えばＤＥＲＰ）の発生或は不発生の証拠は特定の刺激への被験者の感応度に関連する。種々の実施例に於いて、ＥＲＰ計測値はマーケティング及びエンタテインメントの刺激の提出に応じ、ＥＥＧ時間−周波数計測値（ＥＲＰＳＰ）を使用して向上される。特定の部分が抽出され、分離されて実行されるＥＲＰ，ＤＥＲＰ，及びＥＲＰＳＰが特定される。特種の実施例に於いては、注意力、感情、及び記憶保持（ＥＲＰＳＰ）のＥＥＧ周波数推定が共因子としてＥＲＰ，ＤＥＲＰ，及び時間−領域応答解析の向上に使用される。 Evidence for the occurrence or non-occurrence of a particular time domain difference event-related potential component (eg, DERP) at a particular site is related to the subject's sensitivity to a particular stimulus. In various embodiments, ERP measurements are enhanced using EEG time-frequency measurements (ERPSP) in response to submission of marketing and entertainment stimuli. A specific part is extracted, and ERP, DERP, and ERPSP to be executed separately are specified. In particular embodiments, EEG frequency estimation of attention, emotion, and memory retention (ERPSP) is used as a cofactor to improve ERP, DERP, and time-domain response analysis.
ＥＯＧは眼球衝動を計測して刺激の特定した対象への注意力の存在を決定する。眼球追跡は被験者の熟視経路、刺激の特定対象の上の位置及び滞留を計測する。種々の実施例に於いて、ＥＯＧ及び眼球追跡は、眼球衝動到来の勾配で誘発された後頭部及び線条体外領域内の現行ＥＥＧ内のラムダ波（眼球衝動効率の神経生理学的指数）の存在を計測し、ＥＯＧ及び眼球追跡計測値の効率を推測することにより向上される。特種の実施例に於いては、眼球衝動到来に先行した緩慢な電位移動及びＦＥＦ（Ｆｒｏｎｔａｌ Ｅｙｅ Ｆｉｅｌｄ）領域での時間−周波数コヒーレンスの値が計測され眼球衝動活動のデータの効率が向上される。 The EOG measures eyeball impulses to determine the presence of attention to the target identified by the stimulus. Eye tracking measures the subject's gaze path, position on the specific object of the stimulus, and retention. In various embodiments, EOG and eye tracking can be performed to determine the presence of lambda waves (the neurophysiological index of eye impulse efficiency) within the current EEG in the occipital and extrastriatal regions induced by the gradient of the eye impulse arrival. It is improved by measuring and estimating the efficiency of EOG and eye tracking measurements. In a specific embodiment, the value of time-frequency coherence in a slow potential transfer and FEF (Front Eye Field) region prior to the arrival of the eye impulse is measured to improve the efficiency of the eye impulse activity data.
ＧＳＲは典型的に提供された刺激に応じた一般的興奮の変化を測定する。種々の実施例に於いて、ＧＳＲはＥＥＧ／ＥＲＰ応答及びＧＳＲ計測を関連して被験者の用務を向上することで向上される。ＧＳＲ潜在ベースラインが刺激への時間的相関ＧＳＲ応答の構成に使用される。時間的相関ＧＳＲ応答はＥＥＧ計測と共因子化されてＧＳＲ計測値が向上される。 GSR typically measures changes in general excitement in response to a provided stimulus. In various embodiments, GSR is enhanced by improving the subject's service in conjunction with EEG / ERP responses and GSR measurements. The GSR latent baseline is used to construct a temporally correlated GSR response to the stimulus. The temporal correlation GSR response is cofactored with the EEG measurement to improve the GSR measurement.
種々の実施例に於いて、顔面感情記号化には試験前に種々の感情を表現する個人の顔面筋肉位置及び運動を計測して生成されるテンプレートが使用される。これらの個人に独特な顔面感情記号化テンプレートは個々の応答と比較され、被験者の感情的応答が特定される。特種実施例に於いては、特定周波数帯でのＥＥＧ応答に於ける半球間非対称を評価し、周波数帯相互作用を測定することによって、これら顔面感情記号化測定が向上される。本発明のテクニクに於いては、特種な周波数帯がＥＥＧ応答に於いて有意義であるのみならず、脳の特定領域間の交信に使用される特種な周波数帯が有意義であることが、認められて居る。従って、これらのＥＥＧ応答はＥＭＧ，図形的、及びビデオに基づく顔面感情特定を向上する。 In various embodiments, facial emotion symbolization uses a template generated by measuring an individual's facial muscle position and movement that expresses various emotions prior to testing. These individual facial emotion symbolization templates are compared to individual responses to identify the subject's emotional response. In a special embodiment, these facial emotion symbolization measurements are improved by evaluating the interhemispheric asymmetry in the EEG response in a specific frequency band and measuring the frequency band interaction. In the technique of the present invention, it is recognized that not only special frequency bands are significant in the EEG response but also special frequency bands used for communication between specific regions of the brain. It is. Thus, these EEG responses improve EMG, graphical and video based facial emotion identification.
種々の実施例に於いて、脳の複数領域に於けるＥＲＰ時間領域成分の刺激前と刺激後の差分（ＤＥＲＰ）が６０７に於いて計測される。この差分尺度は刺激に起因する応答を引き出す機構を与えるものである。例えば広告に起因する伝言応答或は複数のブランドに起因するブランド応答は共鳴前及び共鳴後推定を使用して決定される。 In various embodiments, the pre-stimulation difference (DERP) of the ERP time domain component in multiple regions of the brain is measured at 607. This difference scale provides a mechanism for extracting the response due to the stimulus. For example, message responses due to advertisements or brand responses due to multiple brands are determined using pre-resonance and post-resonance estimation.
６０９に於いて、脳の複数領域に於ける目的対紛乱刺激差分応答（ＤＥＲＰ）が決定される。６１１に於いて、差分応答のイベント関係時間−周波数解析（ＤＥＲＰＳＰ）が使用されて複数の周波数帯に亘って注意力、感情及び記憶保持尺度がアクセスされる。種々の実施例に於いて、この複数の周波数帯にはテータ、アルファ、ベータ、ガンマ、及び高ガンマ、或はカッパが含まれる。６１３に於いて、複数の試行が実施されて共鳴尺度が向上される。 At 609, a target versus disturbed stimulus differential response (DERP) in multiple regions of the brain is determined. At 611, differential response event-related time- frequency analysis (DERPSP) is used to access attention, emotion, and memory retention measures across multiple frequency bands. In various embodiments, the multiple frequency bands include data, alpha, beta, gamma, and high gamma, or kappa. At 613, multiple trials are performed to improve the resonance scale.
６１５に於いて、無線、有線、衛星或はデータ送信可能なその他の種類の通信ネットワークにより送信するデータ通信装置にプロセスされたデータが供給される。データは６１７に於いて共鳴推定装置に供給される。種々の実施例に於いて、データ通信装置は種々の従来のバス、有線ネットワーク、無線ネットワーク、衛星及び専売通信プロトコルのみならず、ファイル転送プロトコル（ＦＴＰ），ハイパテキスト転送プロトコル（ＨＴＴＰ）のようなプロトコルを使用してデータを送信する。種々の実施例に於いて、データはテレコミュニケイション、無線、インタネット、衛星、或はデータ統合及び解析のために複数の被験者位置から情報を搬送可能なその他の通信機構を使用して送られる。この機構はセットトップボクス、コンピュータシステム、受信機、可動装置などに統合されて居てもよい。 At 615, the processed data is provided to a data communication device for transmission over a wireless, wired, satellite, or other type of communication network capable of transmitting data. Data is provided at 617 to the resonance estimator. In various embodiments, the data communication device includes various conventional buses, wired networks, wireless networks, satellites and proprietary communication protocols as well as file transfer protocol (FTP), hypertext transfer protocol (HTTP) and the like. Send data using the protocol. In various embodiments, data is sent using telecommunication, wireless, internet, satellite, or other communication mechanisms that can carry information from multiple subject locations for data integration and analysis. This mechanism may be integrated into the set top box, computer system, receiver, mobile device, etc.
特種の実施例に於いて、データ通信装置は応答統合システム６１７にデータを送信する。種々の実施例に於いて、応答統合システム６１７は経験／刺激への解析された応答を利用可能の刺激及び刺激属性に関する情報と統合する。使用者行為及び調査応答を含む種々の応答も更に収集され統合される。 In a particular embodiment, the data communication device transmits data to the response integration system 617. In various embodiments, the response integration system 617 integrates the analyzed response to experience / stimulus with information about available stimuli and stimulus attributes. Various responses are also collected and integrated, including user actions and survey responses.
種々の実施例に於いて、応答統合システムは、種々の実体や目的物の位置、運動、加速度、及び空間的関係のような刺激材料属性に関する情報を使用しながら、解析され向上された応答を刺激材料と結合する。特種の実施例に於いて、応答統合システムは消費者経験パタンをより効率的に査定出来るように、使用者行為及び調査応答を収集して解析され向上された応答データと更に統合する。 In various embodiments, the response integration system can analyze and improve responses using information about stimulus material attributes such as position, motion, acceleration, and spatial relationships of various entities and objects. Combine with stimulating material. In a particular embodiment, the response integration system collects user behavior and survey responses and further integrates them with the analyzed and enhanced response data so that consumer experience patterns can be more efficiently assessed.
種々の実施例に於いて、消費者経験査定システムはデータを異なるエンタテインメント、マーケティング、広告，及びその他の聴覚的／視覚的／触覚的／嗅覚的材料への人口統計的、統計的、及び／或は調査に基づく応答の収集及び貯蔵のための消費者経験貯蔵装置６１９へ供給する。もしこの情報が外部的に貯蔵される場合、このシステムには質問、抽出、記録、変更及び／或は更新を含みそれに限定されないデータのプッシュ及び／或はプル統合の為の機構を含むことが出来る。このシステムは人口統計／統計的／調査に基づく応答のような呈上された材料の為の必要条件、査定された神経生理学的及び神経行為的応答尺度、及び追加的刺激属性を全体消費者経験の為の合成尺度へと統合するものである。 In various embodiments, the consumer experience assessment system can provide demographic, statistical, and / or data to different entertainment, marketing, advertising, and other audio / visual / tactile / olfactory materials. Provides a consumer experience store 619 for survey-based response collection and storage. If this information is stored externally, the system may include a mechanism for data push and / or pull integration including but not limited to querying, extraction, recording, modification and / or updating. I can do it. This system provides requirements for presented materials such as demographic / statistical / survey-based responses, assessed neurophysiological and neuroactive response measures, and additional stimulus attributes for overall consumer experience It integrates into a composite scale for
種々の実施例に於いて、消費者経験貯蔵装置は刺激材料の時間的、空間的、活動及びイベントに基づく成分を貯蔵するものである。例えば、神経応答データ、統計的データ、調査に基づく応答データ、及び人口統計的データが集成され貯蔵されて、ビデオストリームの中の特別の成分に関連されてもよい。成分の例には、製品について話して居る、製品について見て居る、製品を買っている、パッケージを開けている、製品に触れている、及び製品を使用している使用者が含まれてよい。別の例として、成分にはソーダの缶を持って居る人を見て居ること、缶の蓋を開けるのを聞くこと、飲み物がつがれるに当たって泡の立つのを眺めること、及び誰かがその飲み物を飲むのを見ることが含まれてよい。成分の各々は有意義的に異なる査定尺度を引き出すものであってよい。 In various embodiments, the consumer experience storage device stores components based on the temporal, spatial, activity and event of the stimulating material. For example, neural response data, statistical data, survey-based response data, and demographic data may be aggregated and stored and associated with particular components in the video stream. Examples of ingredients may include users who are talking about the product, looking at the product, buying the product, opening the package, touching the product, and using the product . As another example, ingredients include watching a person who has a soda can, listening to the can open, watching the foam rising as the drink is tucked, and someone drinking the drink Watching to drink may be included. Each of the components may derive a meaningfully different assessment scale.
図７は消費者経験を推定するテクニクを示す。種々の実施例に於いて、異なるモダリティからの測定が７０１で獲得される。種々の実施例に於いて、ＥＥＧ，ＧＳＲ，ＥＯＧ，ＥＫＧ，ＤＥＲＰ，ＤＥＲＰＳＰ，瞳孔応答などが融合されて結合された尺度が７０３で獲得される。特種の実施例に於いて、融合のために各尺度は適当に整列することが必要かもしれない。種々の実施例に於いて、応答統合システムはモダリティに亘ってデータ解析装置からの異なる尺度を使用し融合する機構を含む。特種の実施例に於いて、データはＥＥＧ，ＧＳＲ，ＥＯＧ，ＥＫＤ，ＤＥＲＰ，ＤＥＲＰＳＰ、瞳孔応答、ＧＳＲ、眼球運動、コヒーレンス、カプリング、及びラムダ波に基づく応答を含む。モダリティに亘る尺度は融合されて使用者共鳴の合成尺度が引き出される。 FIG. 7 illustrates a technique for estimating consumer experience. In various embodiments, measurements from different modalities are obtained at 701. In various embodiments, a combined scale of EEG, GSR, EOG, EKG, DERP, DERPSP, pupil response, etc. is obtained at 703. In particular embodiments, each scale may need to be properly aligned for fusion. In various embodiments, the response integration system includes a mechanism that uses and fuses different measures from the data analyzer across modalities. In particular embodiments, the data includes responses based on EEG, GSR, EOG, EKD, DERP, DERPSP, pupil response, GSR, eye movement, coherence, coupling, and lambda wave. The measures across modalities are merged to derive a composite measure of user resonance.
７０５に於いて神経応答尺度が統計的、人口統計的及び／或は調査に基づく情報と結合される。７０７に於いて、尺度は異なる消費者経験の描写肖像と関連付けされる。場合によっては、或る肖像が他の肖像より有意義的に効果的であると決定されることもある。７０９に於いて、刺激経験の成分が特定される。種々の実施例に於いて、成分は手動及び／或は自動で特定されてよい。場合によって、成分は神経応答
計測間の途切れを見分けることによって特定されてもよい。途切れは有意義な刺激のイベントのないことを示すものかも知れない。他の例に於いて、成分は場面の切れ目或いは画面の有意義的な変化によって識別されてもよい。更に別の例に於いて、成分は刺激材料の供給者によって特定される。イベント、活動、及び経験要素の変化の特定には種々の機構が使用可能である。成分の属性は更に特定されて記録される。属性には活動水準、コントラスト、量、評定、人気度、対象の聴衆、などが含まれてよい。７１３に於いて刺激（統計的、人口統計的、及び／或は調査に基づく）に関する神経生理学的、神経行為的、その他の属性及びメタ情報が成分及び異なる描写肖像の成分の属性に関連付けされる。関連付けされた情報は爾後の解析及び検索のために保存されてもよい。
At 705, neural response measures are combined with statistical, demographic and / or survey-based information. At 707, the scale is associated with descriptive portraits of different consumer experiences. In some cases, one portrait may be determined to be significantly more effective than another. At 709, components of the stimulation experience are identified. In various embodiments, the components may be specified manually and / or automatically. In some cases, a component may be identified by identifying a break between neural response measurements. A break may indicate that there are no meaningful stimulation events. In other examples, the components may be identified by scene breaks or significant changes in the screen. In yet another example, the ingredients are specified by the stimulus material supplier. Various mechanisms can be used to identify changes in events, activities, and experience factors. The component attributes are further specified and recorded. Attributes may include activity level, contrast, quantity, rating, popularity, target audience, and so on. At 713, neurophysiological, neuroactive, and other attributes and meta-information regarding stimuli (based on statistics, demographics, and / or surveys) are associated with attributes of components and components of different depiction portraits . The associated information may be saved for later analysis and retrieval.
消費者経験査定システムは更にプロフィルを洗練し時間に亘って特種な刺激或は刺激の連続への返答の変化を追跡する適応的習得部品を含むことが出来る。 The consumer experience assessment system can further include an adaptive learning component that refines the profile and tracks changes in response to specific stimuli or stimulus sequences over time.
種々の実施例に於いて、データ収集機構、モダリティ内合成機構、モダリティ間合成機構などのような種々の機構は複数の装置に実装される。しかし、これらの種々の機構は単一システムにハードウエア、ファームウエア及び／或はソフトウエアとして実装することも可能である。図８は一個以上の機構を実装するのに使用出来るシステムの一例である。例えば図８に示されるシステムは消費者経験査定システムに使用が出来る。 In various embodiments, various mechanisms such as data collection mechanisms, intra-modality synthesis mechanisms, inter-modality synthesis mechanisms, etc. are implemented in multiple devices. However, these various mechanisms can also be implemented as hardware, firmware and / or software in a single system. FIG. 8 is an example of a system that can be used to implement one or more mechanisms. For example, the system shown in FIG. 8 can be used in a consumer experience assessment system.
特種の実施例に於いて、本発明の特種の実施例を実施するのに好適なシステム８００はプロセサ８０１、メモリ８０３、インタフェイス８１１及びバス８１５（例えばＰＣＩバス）を含むものである。適当なソフトウエア或はファームウエアの制御のもとで運行して居る場合、パタン生成のようなタスクの責任はプロセサ８０１にある。プロセサ８０１の代わりとし、或はプロセサ８０１に追加的に、種々の特別に構成された装置も使用可能である。カストマイズされたハードウエアによっても完全実施は可能である。インタフェイス８１１は典型的にネットワークを通じてデータパケット或はデータ切片を送信したり受信したりするように構成されて居る。装置に支持される特種例のインタフェイスにはホストバスアダプタ（ｈｏｓｔ ｂｕｓ ａｄａｐｔｅｒ（ＨＢＡ））インタフェイス、イーサネット（登録商標）インタフェイス、フレイムリレイ（ｆｒａｍｅ ｒｅｌａｙ）インタフェイス、ケーブルインタフェイス、ＤＳＬインタフェイス、トークンリング（ｔｏｋｅｎ ｒｉｎｇ）インタフェイスなどが含まれる。
In particular embodiments, a system 800 suitable for implementing particular embodiments of the present invention includes a
更に、高速イーサネットインタフェイス、ギガビットイーサネットインタフェイス、ＡＴＭインタフェイス、ＨＳＳＩインタフェイス、ＰＯＳインタフェイス、ＦＤＤＩインタフェイス、などのような種々の非常に高速のインタフェイスが供されてもよい。一般に、これらのインタフェイスは適当なメディアとの交信に適当なポートを含んでもよい。場合によっては独立プロセサを含んでもよく、揮発性ＲＡＭであってもよい。独立プロセサはデータ合成のような交信集中的タスクを制御することが出来る。 In addition, various very high speed interfaces such as high speed Ethernet interfaces, Gigabit Ethernet interfaces, ATM interfaces, HSSI interfaces, POS interfaces, FDDI interfaces, etc. may be provided. In general, these interfaces may include appropriate ports for communication with appropriate media. In some cases, an independent processor may be included, or a volatile RAM. Independent processors can control communication-intensive tasks such as data synthesis.
特種の実施例に於いて、システム８００はデータ、アルゴリズム、及びプログラム使用法の記録にメモリ８０３を使用する。プログラム使用法とは、例えばオペレイティングシステムの操作、及び／或は一つ以上のアプリケイションを制御するものであってよい。一個以上のメモリは受信されたデータ及び作用受信データを記録するように構成されたものであってよい。
In a particular embodiment, system 800 uses
このような情報やプログラム使用法は此処で記述されたシステム／方法を実施するのに使用され得るので、本発明は此処に記載された種々の操作を実施するためのプログラム使用法、状態情報などを含む有形な機械で読む事の出来るメディアに関するものである。機械で読む事の出来るメディアの例にはハードディスク、フロッピイディスク、及び磁気テープのような磁気メディア、ＣＤ−ＲＯＭディスクやＤＶＤのような光学メディア、光学ディスクのような磁気光学的メディア、及びＲＯＭやＲＡＭのようなプログラム使用法の記録及び実施用に特に構成されたハードウエア装置を含むが、それに限られるものではない。プログラム使用法はコンパイラによって生成される機械コード及び翻訳機を使用してコンピュータによって実施され得る高レベルのコードの双方を含むものである。 Since such information and program usage can be used to implement the systems / methods described herein, the present invention provides program usage, status information, etc. for performing the various operations described herein. It relates to media that can be read by tangible machines including Examples of machine-readable media include magnetic media such as hard disks, floppy disks, and magnetic tape, optical media such as CD-ROM disks and DVDs, magneto-optical media such as optical disks, and ROM. Including, but not limited to, hardware devices specifically configured for recording and implementing program usage, such as RAM and RAM. Program usage includes both machine code generated by a compiler and high level code that can be implemented by a computer using a translator.
本発明は明確に理解されるべく詳細に亘って記述されたものであるが、此処に添付するクレームの範囲内に於いて、若干の変更が可能であることは明白であろう。従って、この開示は例示的なもので、限定的なものではないと解釈されるべきものであり、発明は此処に示された詳細に限定されず、添付されたクレームと均等の範囲内で変更され得るものと解釈すべきものである。
本発明は、たとえば、以下のような態様で実現することもできる。
適用例１
複数のモダリティを有し、上記複数のモダリティを使用して複数の成分を含む刺激材料に曝された消費者から神経応答データを獲得する機能を有するデータ収集装置と、
上記刺激材料の複数の成分の各々についての消費者経験を査定する機能を有し、上記複数のモダリティからの結合された神経応答データを使用して消費者経験を査定する機能をする応答統合システムと、を有する、システム。
適用例２
上記複数のモダリティがＥＥＧとＥＯＧとを含む、適用例１のシステム。
適用例３
上記複数のモダリティが更にＧＳＲとＥＫＧとを含む、適用例２のシステム。
適用例４
上記データ収集装置が、脳の複数領域に於けるＥＲＰ時間領域成分の差分測定（ＤＥＲＰ）を決定するために目的と紛乱ＥＲＰ測定を得るように更に機能可能である、適用例１のシステム。
適用例５
上記データ収集装置が、差分測定のイベント関係時間−周期数解析を獲得し、複数の周期数帯に亘って注意力、感情、及び記憶保持を査定する（ＤＥＲＰＳＰ）ように更に機能可能である、適用例１のシステム。
適用例６
上記複数の周期数帯がテータ、アルファ、ベータ、ガンマ、及び高ガンマを含むものである、適用例５のシステム。
適用例７
上記刺激材料の成分がイベントを含むものである、適用例１のシステム。
適用例８
上記刺激材料の成分が刺激材料の感覚的経験を含むものである、適用例７のシステム。
適用例９
上記刺激材料の成分が製品を観察すること、製品を開けること、及び製品を消費する事を含むものである、適用例７のシステム。
適用例１０
神経応答データが上記刺激材料の成分と相関するものである、適用例７のシステム。
適用例１１
第一モダリティからの神経応答データが第二モダリティからの神経応答データと整列されて結合されるものである、適用例１のシステム。
適用例１２
第一モダリティからの神経応答データの第二モダリティからの神経応答データへの整列が時間及び位相移動を含むものである、適用例１１のシステム。
適用例１３
複数のモダリティを使用して複数の成分を含む刺激材料に曝された消費者から神経応答データを獲得する工程と、
上記複数のモダリティからの神経応答データを結合された神経応答データへ統合する工程と、
上記複数のモダリティからの結合された神経応答データを使用して消費者経験を上記刺激材料の上記複数の成分の各々について査定する工程と、を備える方法。
適用例１４
上記複数のモダリティがＥＥＧとＥＯＧとを含む、適用例１３の方法。
適用例１５
上記複数のモダリティが更にＧＳＲとＥＫＧとを含む、適用例１４の方法。
適用例１６
データ収集装置が、脳の複数領域に於けるＥＲＰ時間領域成分の差分測定（ＤＥＲＰ）を決定するために目的と紛乱ＥＲＰ測定を得るように更に機能可能である、適用例１３の方法。
適用例１７
複数のモダリティを使用して複数の成分を含む刺激材料に曝された消費者から神経応答データを獲得する手段と、
上記複数のモダリティからの神経応答データを結合された神経応答データへ統合する手段と、
上記複数のモダリティからの結合された神経応答データを使用して消費者経験を上記刺激材料の上記複数の成分の各々について査定する手段と、を有するシステム。
While the invention has been described in detail for purposes of clarity of understanding, it will be apparent that certain modifications may be made within the scope of the claims appended hereto. Accordingly, the disclosure is to be construed as illustrative and not restrictive, and the invention is not limited to the details set forth herein but may be modified within the scope equivalent to the appended claims. Should be construed as being possible.
The present invention can also be realized in the following manner, for example.
Application example 1
A data collection device having a plurality of modalities and having a function of acquiring neural response data from a consumer exposed to a stimulation material containing a plurality of components using the plurality of modalities;
A response integration system having the function of assessing consumer experience for each of the plurality of components of the stimulating material and functioning to assess consumer experience using combined neural response data from the plurality of modalities And having a system.
Application example 2
The system according to application example 1, wherein the plurality of modalities include EEG and EOG.
Application example 3
The system of application example 2, wherein the plurality of modalities further include GSR and EKG.
Application example 4
The system of application example 1, wherein the data collection device is further operable to obtain objective and perturbed ERP measurements to determine differential measurements (DERP) of ERP time domain components in multiple regions of the brain.
Application example 5
The data collection device is further operable to acquire a differential measurement event-related time-period number analysis and to assess attention, emotion, and memory retention (DERPSP) over multiple period bands, The system of application example 1.
Application Example 6
The system of application example 5, wherein the plurality of period bands include data, alpha, beta, gamma, and high gamma.
Application example 7
The system of application example 1, wherein the component of the stimulation material includes an event.
Application example 8
The system of application example 7, wherein the components of the stimulation material include sensory experience of the stimulation material.
Application example 9
The system of application example 7, wherein the components of the stimulating material include observing the product, opening the product, and consuming the product.
Application Example 10
The system of application example 7, wherein neural response data correlates with components of the stimulating material.
Application Example 11
The system of application 1, wherein neural response data from the first modality is aligned and combined with neural response data from the second modality.
Application Example 12
The system of application 11, wherein the alignment of neural response data from the first modality to neural response data from the second modality includes time and phase shift.
Application Example 13
Obtaining neural response data from a consumer exposed to a stimulating material comprising a plurality of ingredients using a plurality of modalities;
Integrating neural response data from the plurality of modalities into combined neural response data;
Assessing consumer experience for each of the plurality of components of the stimulating material using combined neural response data from the plurality of modalities.
Application Example 14
The method of application example 13, wherein the plurality of modalities include EEG and EOG.
Application Example 15
The method of application example 14, wherein the plurality of modalities further include GSR and EKG.
Application Example 16
The method of application example 13, wherein the data acquisition device is further operable to obtain objective and perturbed ERP measurements to determine differential measurements (DERP) of ERP time domain components in multiple regions of the brain.
Application Example 17
Means for acquiring neural response data from a consumer exposed to a stimulating material comprising a plurality of ingredients using a plurality of modalities;
Means for integrating neural response data from the plurality of modalities into combined neural response data;
Means for assessing consumer experience for each of the plurality of components of the stimulating material using combined neural response data from the plurality of modalities.
Claims (20)
上記広告、上記エンタテインメント、または上記活動の各感覚的成分についての上記複数のモダリティからの神経応答データを結合して、上記広告、上記エンタテインメント、または上記活動の上記複数の感覚的成分についての消費者経験を査定する応答統合システムと、を有する、システム。 A data collection device having a function of acquiring neural response data for a plurality of modalities from a consumer exposed to an advertisement , entertainment , or activity including a plurality of sensory components, wherein the neural response data is the advertisement , A data collection device obtained for the entertainment or the sensory components of the activity ;
The advertisement, by combining the neural response data from the plurality of modalities for each sensory components of the entertainment or the activity, the consumption of the advertisement, the entertainment or information on said plurality of sensory components of the activities, A response integration system for assessing a person's experience.
上記広告、上記エンタテインメント、または上記活動の上記複数の感覚的成分について上記複数のモダリティからの神経応答データを、結合された上記神経応答データへ統合する工程と、
結合された神経応答データに基づいて、上記広告、上記エンタテインメント、または上記活動の上記複数の感覚的成分について消費者経験を査定する工程と、を備える方法。 Ads with multiple sensory component, comprising the steps of accessing the neuro-response data collected using a plurality of modalities of entertainment or consumer exposed to activity, the neural response data the advertisement, corresponding to said plurality of sensory components of the entertainment or the activity, comprising the steps,
Integrating neural response data from the modalities into the combined neural response data for the plurality of sensory components of the advertisement , the entertainment , or the activity ;
Assessing consumer experience for the plurality of sensory components of the advertisement , the entertainment , or the activity based on combined neural response data.
前記目的イベント関係電位測定と前記紛乱イベント関係電位測定とに基づいて、差分イベント関係電位測定を決定することと、を更に含む、請求項１０に記載の方法。 Calculating a target event related potential measurement and a disruptive event related potential measurement ;
On the basis of the purpose and event related potential measurement and the Funran event related potential measurement, and determining the difference events related potential measurement, further comprising a method according to claim 10.
上記製品を見ることおよび開けることの少なくとも一つの上記複数の感覚的成分について上記複数のモダリティからの上記神経応答データを、結合された神経応答データへ統合する手段と、
上記複数のモダリティからの結合された神経応答データに基づいて、上記製品を見ることおよび開けることの少なくとも一つの上記複数の感覚的成分について消費者経験を査定する手段と、を有するシステム。 And at least one opening the can and the product see the product, including a plurality of sensory component, a plurality of modalities of consumers exposed to at least one of to open it and Product View Product and means for accessing the neural response data collected using, the neural response data corresponding to each of at least one of said plurality of sensory components to open Rukoto and viewed the product, and means ,
Means for integrating the neural response data from the plurality of modalities into combined neural response data for at least one of the plurality of sensory components of viewing and opening the product;
System with on the basis of the combined neural response data from the plurality of modalities, the means for assessing at least one consumer experience with the plurality of sensory components and that the opening can see the product, the.
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- 2008-08-27 CN CN2008801049821A patent/CN101795620B/en active Active
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- 2008-08-27 KR KR1020107003052A patent/KR20100047865A/en not_active Application Discontinuation
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| KR20100047865A (en) | 2010-05-10 |
| EP2180825A1 (en) | 2010-05-05 |
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| CN101795620B (en) | 2013-05-01 |
| US8392254B2 (en) | 2013-03-05 |
| US20090063255A1 (en) | 2009-03-05 |
| EP2180825A4 (en) | 2013-12-04 |
| CN101795620A (en) | 2010-08-04 |
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